LLM Mart Basic

Add, review, or fix JavaScript interop in Blazor components. USE FOR: calling JavaScript from Blazor, calling .NET from JavaScript, collocated .razor.js modules, IJSRuntime, IJSObjectReference lifecycle, DotNetObjectReference, ElementReference, timing rules for when JS is availab

Imperative guidance for the System.Text.Json APIs added in .NET 11: the built-in `JsonNamingPolicy.PascalCase` naming policy, and the strongly-typed `JsonSerializerOptions.GetTypeInfo<T>()` and `JsonSerializerOptions.TryGetTypeInfo<T>(out JsonTypeInfo<T>? info)` metadata accessor

Author and review GitHub Actions workflow YAML safely so syntactically-valid YAML can't ship a workflow that GitHub Actions refuses to run. USE FOR: editing, adding, or reviewing any file under .github/workflows/, writing run-name/name/if/env/run values that contain ${{ }} expres

Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.

Scaffolds new agent skills for the dotnet/skills repository. Use when creating a new skill, generating SKILL.md files, writing a skill description that the runtime will actually route to, or setting up skill directory structures. Handles frontmatter generation, section templates,

Scaffolds eval.yaml evaluation specs for agent skills in the dotnet/skills repository. Use when creating skill tests, writing evaluation stimuli, defining graders and rubrics, sizing an eval for statistical power, or setting up test fixture files. Handles the Vally eval.yaml sche

Diagnoses and fixes skills in the dotnet/skills repository that lose to their own baseline, fail to activate, time out, or return "no credible improvement". Use when an evaluation verdict is a regression or underpowered, when a skill regressed after a change, when /evaluate repor

Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.

Audits .NET test mock usage by tracing each mock setup through the production code's execution path to find dead, unreachable, redundant, or replaceable mocks. Use when the user asks to audit mock usage, find unused or unnecessary mock setups, check if mocks are needed, reduce mo

Detects duplicate boilerplate, copy-paste tests, and structural maintainability issues across .NET test suites. Use when the user asks to reduce repetition, consolidate similar test methods, convert copy-paste tests to data-driven parameterized tests, suggest a better test struct

GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.

Analyzes .NET code for performance bottlenecks, recommends concrete optimizations, and guides benchmarking. Scans for ~50 anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O. Use when reviewing .NET code performance, optimizing hot paths,

Agent for diagnosing and optimizing MSBuild build performance. Runs multi-step analysis: generates binlogs, analyzes timeline and bottlenecks, identifies expensive targets/tasks/analyzers, and suggests concrete optimizations. Invoke when builds are slow or when asked to optimize

Agent that reviews MSBuild project files for anti-patterns, modernization opportunities, and best practices violations. Scans .csproj, .vbproj, .fsproj, .props, .targets files and produces actionable improvement suggestions. Invoke when asked to review, audit, or improve MSBuild

Expert agent for MSBuild and .NET build troubleshooting, optimization, and project file quality. Routes to specialized agents for performance analysis and code review. Verifies MSBuild domain relevance before deep-diving. Specializes in build configuration, error diagnosis, binar

Expert agent for .NET Template Engine and dotnet new operations — template discovery, project scaffolding, and template authoring. Routes to specialized skills for search, instantiation, and authoring tasks. Verifies template-engine domain relevance before deep-diving.

Orchestrates .NET test framework and platform migrations: auto-detects the current framework and version, routes to the appropriate migration skill, and guides users through end-to-end upgrades. Use when asked to upgrade MSTest, migrate to xUnit v3, switch to Microsoft.Testing.Pl

Runs build/compile commands for any language and reports results. Use when: compiling code, running dotnet build, checking for compilation errors, verifying project builds successfully.

Fixes compilation errors in source or test files. Use when: resolving build errors, fixing CS/TS error codes, adding missing imports, correcting type mismatches, fixing compilation failures.

Internal implementation agent for the code-testing-agent skill. Orchestrates the Research-Plan-Implement pipeline after that public entry-point skill delegates a test-generation request. Do not route user prompts here directly.

Fourteen posts of being wrong in production, compressed to checkboxes

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

Generate API documentation from code

Update or generate YAML documentation for SQL models with proper descriptions and tests

Configure end-to-end testing suite

Generate accurate project time estimates

Analyze and explain code functionality

Explain how tasks in an issue were implemented with detailed breakdown

Search and locate tasks across all orchestrations using various criteria.

Apply the Five Whys root cause analysis technique to systematically investigate issues

Analyze and fix a GitHub issue with comprehensive testing and verification

Fix a specific issue or problem with the given identifier or description

Fetch unresolved comments for current branch's PR and fix them

Generate and analyze future scenarios with plausibility scoring, trend integration, and uncertainty quantification.

Auto-generate API reference documentation

You are tasked with generating a technical work log comment for a Linear issue based on recent git commits.

Generate comprehensive test cases automatically

Generate comprehensive test suite for $ARGUMENTS following project testing conventions and best practices.

Show detailed git repository status

Deploy critical hotfixes quickly

Verify repository is in working state by running CI checks and fixing issues

Design and implement caching solutions

PiG (Pi in Go) is a faithful Go port of upstream Pi, the TypeScript codebase behind the Pi coding agent. It is a parity-bound translation, not a rewrite: upstre…

An AI Agent that lives in your pocket. Local-first and privacy focused.

Unofficial skill that teaches coding agents to build with TypeSafe AI's Jev: typed decisions, calibrated confidence, and prior art from 150+ community projects.

Adaptive Test-time Learning and Autonomous Specialization

Prediction-market trading engine — Wang Transform pricing on 291K+ contracts; paper-traded across Kalshi · Polymarket · Solana DFlow (Jito bundles) · 633 tests

Knowledge Management for Humans and Agents

Open-source Claude Cowork / Codex / WorkBuddy alternative — a local-first AI office agent that turns one request into real PPTX, DOCX, XLSX and HTML files. Runs…

DeepAgent Code: AI coding agent with persistent memory and control plane

Awesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.

CLI for Telegram — agent-friendly, daemon-based, with webhook event push.

AI deep-research agent that turns any question into a cited report: plans searches, reads real sources, verifies evidence. Self-hosted, multi-provider, Docker-r…

Event-stream AI Agent framework for building your persona bot 🍊

Give the agent a machine. Just not yours. Each AI coding agent gets its own isolated machine with root, Docker, and systemd - active defense detects and stops t…

Local Emperor-style AI agent with Vue WebUI, multi-provider LLMs, streaming chat, tools, skills, memory, and token telemetry.

Open-source AI reverse-engineering agent platform and MCP server for Ghidra, Frida, x64dbg and Rizin — automated PE/APK/binary analysis, CTF and malware researc…

"Never send a human to do a machine's job" - Open Source AI hacking agent

Prismer Cloud

My Personal Blog (Robotics)

Tau Coding Agent - like Pi, but twice as much

Open-source alternative to OpenAI Dots: self-hosted AI chat, tools, approvals, connectors, and computer tasks.